That's pretty cool. Plants basically arrange tiny ridges and bumps that act like a low‑cost ray‑tracing algorithm, scattering light and keeping more photons in the photosynthetic zone. I could see modeling that with a simple recursive grid if you want to dig into the math.

Sure, let’s set up a simple 2‑D grid. Each cell represents a patch of leaf. We'll define a scattering matrix S that maps incoming light intensity I to outgoing intensity I′. If we add a ridge pattern, we change S locally—say, double the transmission coefficient along the ridge axis. Then we can iterate: I_{n+1}=S·I_n, starting from a uniform illumination vector. After a few iterations you’ll see the intensity concentrates along the ridges, mimicking the plant’s natural efficiency. If you want, I can write the pseudocode for the recursion.

Here’s a very compact version you can copy straight into any language that supports matrix operations or just arrays. ``` // grid size N = 100 // e.g., 100×100 leaf patch // light vector (initially uniform) I[n] = 1.0 for all n // scattering matrix S (NxN) – initialize to base transmission for i from 0 to N-1 for j from 0 to N-1 if i == j S[i][j] = 0.8 // basic absorption else if abs(i-j) == 1 // neighbor coupling S[i][j] = 0.05 // add ridge pattern: double transmission along a row or column ridgeRow = 40 for j from 0 to N-1 S[ridgeRow][j] *= 2 // iterate until steady state or max steps maxIter = 50 for t from 1 to maxIter Inew[n] = sum over k (S[n][k] * I[k]) I = Inew // after loop, I contains the trapped light distribution ``` Adjust `ridgeRow` and the factor in the `if` block to match the ridge geometry of real leaves. The key is that the matrix S encodes how much light moves from one patch to another; by boosting a row or column you simulate the ridge’s extra scattering, and the iteration makes the pattern settle into its natural efficiency. Feel free to tweak the values – even a small change in transmission can make a big difference once the system runs through several iterations.